用脑电波指挥机器人走迷宫，老人只需看一眼就能完成家务
Neural Signal Operated Intelligent Robot: Human-guided Robot Maze Navigation through SSVEP
- 通过脑电视觉诱发电位实现人眼注视控制机器人导航
- 系统可实时运行，显著缩短迷宫求解时间
- 适合老年群体，无需肢体操作，易用于居家辅助
基于稳态视觉诱发电位（SSVEP）的脑机接口具有快速、准确、便携的优点。SSVEP 是由特定频率视觉刺激诱发的脑电响应，在对应频率处脑电信号增强。本文提出一种新型基于 SSVEP 的人眼引导迷宫求解机器人导航系统。利用人类对迷宫整体结构的直观认知，结合脑电信号控制机器人路径选择，显著减少迷宫求解时间。方法包括离线训练 SSVEP 分类模型、实现机器人自主导航算法，并在线部署以支持实时操作。实验结果表明该系统可行，未来有望帮助众多老年人仅通过眼神即可在家中完成简单日常任务。
原文摘要 · Abstract (English)
Brain-computer Interface (BCI) applications based on steady-state visual evoked potentials (SSVEP) have the advantages of being fast, accurate and mobile. SSVEP is the EEG response evoked by visual stimuli that are presented at a specific frequency, which results in an increase in the EEG at that same frequency. In this paper, we proposed a novel human-guided maze solving robot navigation system based on SSVEP. By integrating human's intelligence which sees the entirety of the maze, maze solving time could be significantly reduced. Our methods involve training an offline SSVEP classification model, implementing the robot self-navigation algorithm, and finally deploy the model online for real-time robot operation. Our results demonstrated such system to be feasible, and it has the potential to impact the life of many elderly people by helping them carrying out simple daily tasks at home with just the look of their eyes.
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